Internet and database searching with handheld devices

ABSTRACT

The presently claimed invention relates to network searching and handheld devices. One claim recites a method including: from a first wireless device, wirelessly communicating with a second wireless device to determine whether the second wireless device has performed an internet or database search; receiving, at the first wireless device, information from the second wireless device regarding the internet or database search, if the information satisfies predetermined criteria on the first wireless device, requesting from the second wireless device at least a subset of results obtained from the internet or database search. Another claim recites: a method of searching comprising: receiving search criteria in a first, handheld mobile device; upon sensing a second, handheld mobile device by the first, handheld mobile device, automatically and wirelessly querying the second, handheld mobile device to determine whether the second, handheld mobile device has any content stored thereon corresponding to the search criteria; and receiving content corresponding to the search criteria from the second, handheld mobile device. Of course, other claims and combinations are also provided.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This application is a Continuation of U.S. application Ser. No.12/211,620, filed Sep. 16, 2008, which is a Continuation of U.S.application Ser. No. 11/152,684, filed Jun. 13, 2005, which claimspriority from U.S. Provisional Application 60/582,280, filed Jun. 22,2004, U.S. application Ser. No. 11/152,684 also claims priority fromU.S. Provisional Application 60/656,642, filed Feb. 25, 2005, and U.S.application Ser. No. 11/152,684 also claims priority from U.S.Provisional Application 60/673,022, filed Apr. 19, 2005, all of whichare incorporated herein by reference in their entireties.

TECHNICAL FIELD

The present invention relates generally to mobile devices. In someimplementations the present invention relates to digital watermarking,searching networks or desktops.

BACKGROUND AND SUMMARY

As digital content continues to proliferate, management of digitalassets becomes an increasingly difficult challenge. Enhancements incomputer networking and database technology allow companies to managelarge collections of images and other media and make the contentavailable to third parties. While network communication provides apowerful tool to enable a database manager to share content with others,it makes it more difficult to control and track how the content is beingused, and efficiently share the content.

Prior patent documents by the assignee of this patent applicationdescribe systems and methods of automated searching and digitalwatermark screening of media object files on computer networks like theinternet. See, e.g., assignee's U.S. Pat. No. 5,862,260, which is herebyincorporated by reference. Software used to perform automated searchingand compiling of internet content or links is sometimes referred to as aweb crawler or spider.

Digital watermarking is a process for modifying media content to embed amachine-readable code into the data content. The data may be modifiedsuch that the embedded code is imperceptible or nearly imperceptible tothe user, yet may be detected through an automated detection process.Most commonly, digital watermarking is applied to media such as images,audio signals, and video signals. However, it may also be applied toother types of data, including documents (e.g., through line, word orcharacter shifting, background texturing, etc.), software,multi-dimensional graphics models, and surface textures of objects.

Digital watermarking systems have two primary components: an embeddingcomponent that embeds the watermark in the media content, and a readingcomponent that detects and reads the embedded watermark. The embeddingcomponent embeds a watermark by altering data samples of the mediacontent in the spatial, temporal or some other domain (e.g., Fourier,Discrete Cosine or Wavelet transform domains). The reading componentanalyzes target content to detect whether a watermark is present. Inapplications where the watermark encodes information (e.g., a message),the reader extracts this information from the detected watermark.

The present assignee's work in steganography, data hiding and digitalwatermarking is reflected, e.g., in U.S. Pat. Nos. 5,862,260, 6,408,082and 6,614,914; and in published specifications WO 9953428 and WO 0007356(corresponding to U.S. Pat. Nos. 6,449,377 and 6,345,104). A great manyother approaches are familiar to those skilled in the art. The artisanis presumed to be familiar with the full range of literature concerningsteganography, data hiding and digital watermarking. The subject matterof the present application is related to that disclosed in U.S. Pat.Nos. 5,862,260, 6,122,403 and in co-pending application Ser. No.09/571,422 filed May 15, 2000, Ser. No. 09/620,019 filed Jul. 20, 2000,and Ser. No. 09/636,102 filed Aug. 10, 2000; which are herebyincorporated by reference.

As an extension of the watermark-based information retrieval describedin U.S. Pat. No. 5,862,260 and marketed by Digimarc Corporation (e.g.,under the trade name IMAGEBRIDGE), watermark decoders can be employed ina distributed fashion to perform watermark screening and interactingwith watermarked media objects on networks, including the internet. Forexample, watermark decoders are deployed at a variety of locations on acomputer network such as the internet, including in internet searchengines that screen media objects gathered by each search engine,network firewalls that screen media objects that are encountered at thefirewall, in local area networks and databases where spiders do nottypically reach, in content filters, in client-based web-browsers, etc.Each of these distributed decoders acts as a spider thread that logs(and perhaps acts upon) watermark information. Examples of the types ofwatermark information include identifiers decoded from watermarks inwatermarked media objects, media object counts, addresses of thelocation of the media objects (where they were found), and other contextinformation (e.g., how the object was being used, who was using it,etc.). The spider threads, in turn, send their logs or reports to acentral spider program that compiles them and aggregates the informationinto fields of a searchable database.

But the internet is vast. One challenge is to locate watermarked contentthroughout the web.

Thus, additional improvements are provided to even further explore thedepths of the internet for watermark data.

Another challenge is to find and manage content stored locally on auser's computer or on her networked computers. Searching tools haverecently emerged to allow a user to search and catalog files on hercomputer. Examples are Google's Google Desktop Search and Microsoft'sMSN Desktop Search. We provide improvements to ensure that metadataassociated with images and audio are current and easily indexable bysuch desktop searching tools.

One implementation includes a method including: from a first mobiledevice, wirelessly querying a second mobile device to determine whetherthe second mobile device has internet search results relating topredetermined search criteria; and receiving at least a subset of thesearch results.

Another implementation includes a method including: from a firstwireless device, wirelessly communicating with a second wireless deviceto determine whether the second wireless device has performed aninternet or database search; receiving, at the first wireless device,information from the second wireless device regarding the internet ordatabase search, if the information satisfies predetermined criteria onthe first wireless device, requesting at least a subset of resultsobtained from the internet or database search.

Yet another implementation includes a method including: receiving searchcriteria in a first, handheld mobile device; upon sensing a second,handheld mobile device by the first, handheld mobile device,automatically and wirelessly querying the second, handheld mobile deviceto determine whether the second, handheld mobile device has any contentstored thereon corresponding to the search criteria; and receivingcontent corresponding to the search criteria from the second, handheldmobile device.

Further aspects, implementations, features and advantages will becomeeven more apparent with reference to the following detailed descriptionand accompanying drawing.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system for enhancing network searching.

FIG. 2 illustrates a desktop searching tool.

FIG. 3 illustrates a metadata repository that communicates with thedesktop searching tool of FIG. 2.

FIG. 4 illustrates associating a person's metadata profile with images.

FIG. 5 illustrates a graphical user interface for selectingautomatically gathered or generated metadata.

FIG. 6 illustrates a metadata authoring tool on a user's desktop.

FIG. 7 is a flow diagram illustrating a desktop indexing methodaccording to yet another aspect of the invention.

DETAILED DESCRIPTION

Introduction

The following sections describe systems and processes for contentsearching, indexing and desktop searching. Some of these employimperceptibly embedded digital watermarks in combination with othermechanisms for identifying and indexing media content, including stillimages, video, audio, graphics, and text. Some of the sections describemethods and systems for automatically generating and gatheringinformation, indexing the information in a searchable index andassociating the information with media files.

Searching More of the Internet and Integrated Searching Systems

Web searching continues to be a boom for the internet. Examples includeGoogle, Yahoo!, and MSNBC, to name a few. Web searching allows a user tofind information that is distributed over the internet. However, currentsearching systems have two major problems. First, web crawlers that findinformation for indexing on a search engine only search around 10-20% (agenerous estimate) of the internet. Second, a web crawler traditionallyonly locates surface information, such as HTML (hypertext markuplanguage) web page, and ignores deep information, including downloadablefiles, FlashMedia and database information.

We are faced with a problem of how to efficiently search the internet.The more internet we search, the higher chance we have of locatingwatermarked content thereon.

A first solution uses an army of client-based web-browsers to locatewatermarked content.

One implementation of this first solution searches content that a userencounters as she routinely surfs the internet. Once identified,watermarked content and a content location can be reported to a centrallocation. The power of this tool emerges as watermark detectors areincorporated into hundreds or thousands (even millions) of browsingtools. Watermarked content—perhaps located behind password protected orrestricted websites—is analyzed after a user enters the website, perhapsafter entering a user id or password to gain access to a restrictedwebsite.

Consider a few additional details. A digital watermark reader isincorporated into (or cooperates with) a user's internet browser or filebrowser, such as Windows Explorer. Using a web file browser equippedwith watermark reader software (e.g., a plug-in, integrated via anApplication Programming Interface, or as a shell extension to theoperating system), a user browses the internet and/or content files. Thedigital watermark reader analyzes content encountered through thebrowser. For example, say a user visits ESPN.com, CNN.com and then looksat images posted on LotsofImages.com. The watermark reader sniffsthrough the various web pages and web images as the user browses thecontent. (A watermark reader can also be configured to review web-basedaudio and video as well.) The digital watermark reader is looking forwatermarked content. Upon finding and decoding watermarked content, thereader obtains a watermark identifier. The identifier can be a numericidentifier or may include text or other identifying information. Thewatermark reader stores (or immediately reports) the identifier and aweb location at which the watermark identifier was found. The report canalso include a day/timestamp.

When the central server receives a location report, the server can,optionally, verify the existence of the watermarked content by visitingthe web location and searching for the watermarked content.Alternatively, the server reports the watermarked content to aregistered owner of the content. The owner is identified, e.g., througha database lookup that associates identifiers with their owners. (Theowner can then use the report to help enforce copyrights, trademarks orother intellectual property rights). The central server can alsomaintain a log—a chain of custody if you will—to evidence thatwatermarked content (e.g., audio, video, images) was found on aparticular day, at a particular web location.

Instead of a watermark reader reporting identified content to a server,the watermark reader can alternatively report the content identifier andlocation directly to an owner of the watermarked content. In thisimplementation, a watermark includes or links to information thatidentifies a content owner. The watermark reader uses this informationto properly direct a message (e.g., automated email) to the owner whenreporting a watermark identifier and location at which the watermarkidentifier was found.

A related implementation of our first solution is a bit more passive. Awatermark reader is incorporated into a browser (or screen saver). Thewatermark-reader-equipped browser searches the internet for watermarkedcontent when the computer is idle or otherwise inactive. For example,the browser automatically searches (e.g., visits) websites when a screensaver is activated, or after a predetermined period of computerinactivity.

But which websites does the browser visit?

There are a number of suitable approaches to direct web browsing.

In a first implementation, a browser (or cooperating software)communicates with a central server to obtain a list of websites tovisit. The browser caches the list, and accesses the websites listedtherein when the computer is inactive. Or, instead of providing aquerying browser a list of websites, the server provides the browserwith a list of keywords. The keywords are plugged into a search engine,say Google, and the browser then searches resulting websites duringperiods of computer inactivity. The browser can be configured to acceptkeywords and automatically access a search engine, where resulting URLsare collected and searched. Or, the central server can hit the searchengine, plug in the keywords, and collect the URLs. (Content owners cancommunicate with the central server, giving it a listing of websites orkeywords that the customers would like to have searched).

Instead of operating during periods of inactivity, awatermark-reader-equipped browser can search as a background process.For example, the browser searches websites while a computer user isfrantically pulling together a PowerPoint presentation or typing email.The background process is optionally interrupted when the user clicksthe browser icon for web browsing or when the user needs additionalcomputer resources. In fact, one implementation of our inventionprovides a regulator (e.g., a software module) to monitor activityassociated with watermark searching. The regulator automatically scalesback watermark searching activity if processing or computer resourcesreach a predetermined level. (A pop-window can also be presented to auser to allow a user to determine whether to continue watermarksearching.)

If a watermark reader encounters a database or flash media (or othercontent that is difficult to analyze), the watermark reader can reportsuch findings to a central server. The central server can revisit thewebsites to handle such layered content. For example, the central servermay employ algorithms that allow databases or FlashMedia to be exploredfor watermarked content. One example of a database is an image database.The database is combed, perhaps with a keyword search for file names ormetadata, or via a record-by-record search. Each record (or specificrecords) is then searched for watermarked content.

Targeted Searching

Efficiencies are leveraged when watermark detection is combined withtargeted searching.

For example, a content owner (e.g., a copyright owner of prize-winningBeagle images) discovers that her images are being copied from herwebsite and illegally distributed on the internet. Of course, thecontent owner embeds her images with digital watermarks prior to postingthem on her website. The watermarks preferably carry or link to imageidentifying information, such as the content owner's name, imageidentifier, data copyright information, etc. The content owner furtherdiscovers that her pirated images are often associated with a particularbrand of knock-off dog food, “Yumpsterlishious.” A targeted search(e.g., via a search engine) for “Yumpsterlishious” and/or “Beagles”generates a listing of, oh say, 1024 URLs. Content from each of the 1024URLs is then analyzed with a watermark reader to locate unauthorizedcopies of the content owner's images. The location (e.g., URL) ofsuspect images can be forwarded to the copyright owner for legalenforcement. Of course, other keywords may include author, photographer,artist, subject matter, dates, etc. The above examples leverage keywordsearching (or targeted searching) and digital watermark analysis.

Another targeted search utilizes metadata associated with content. Asearch engine (or media handlers, like web browsers, media players,etc.) looks for keywords in content metadata (e.g., headers, XML tags,etc.). Content including certain keywords in associated metadata (e.g.,to borrow from the above example, “Beagles”) is searched with awatermark reader to determine whether it includes a watermark embeddedtherein. Or metadata associated with an audio or video file is searchedfor keywords, and if the keywords are found, the file is furtheranalyzed with a digital watermark reader. This example uses keywords inmetadata to identify likely candidates for watermark detection.

We can also combine watermark detection with so-called pattern matching.Pattern matching algorithms are well known, and we can employ suchalgorithms while searching the internet for lexical or image basedmatches. Watermark decoding is performed only on content meetingpredetermined pattern criteria. For example, a pattern matching searchis initiated for all images or graphics including a stylistic X, atrademark for Xerloppy Corporation. The pattern matching search turns up72 hits. The images (or graphic files) are then searched to determinewhether a digital watermark embedded therein.

Yet another targeted searching tool leverages network traffic patterns.Routers and switch nodes are monitored to determine internet traffictrends. A watermark-reading web crawler is directed toward the trends.For example, a particular router is monitored to see where trafficoriginated or is routed from prior to accessing a website includingcopyrighted (and watermarked) images. The suspected originating orrouting websites are crawled in search of watermarked content.

Still another targeted searching method routinely analyzes websites inwhich unauthorized copyrighted materials have been previously found. Forexample, a server maintains a listing of websites where watermarkedcontent has been previously found. The websites are routinely crawled insearch of any watermarked content.

Integrated Searching System

FIG. 1 illustrates a system 101 implementing an integrated searchingstrategy. The term “integrated” is used to reflect a system operable toemploy both manual and automated searching. One object of system 101 isto identify digital watermarked content on a network, like the internet.The system includes a central control panel or interface 102, throughwhich searching criteria is provided. For example, a customer can entersearch terms (e.g., “Beagle”) or specific web addresses that she wouldlike searched for watermarked content through, e.g., a web-basedcustomer interface 104. The terms and/or URLs are communicated tointerface 102. Interface 102 farms the terms and/or URLs to a watermarkdetector-enabled web crawler (or searching agent) 120 or to adistributed watermark detector-enabled web crawler (e.g., a soldier fromthe “army” of web browsers mentioned above). As an alternative,interface 102 provides the terms and/or URLs to directed search module106, which is a server-based web crawler including a digital watermarkdetector. The directed search module 106 hits the corresponding URLs insearch of watermarked content.

The FIG. 1 system further includes a manual searching module 108 inwhich an operator directs searching. For example, an operator enters awebsite to be forwarded to web crawler 120, or directs a web browser toa particular website in search of watermarked content. Or, the module108 is used to interface with a search engine, e.g., Google, wherekeywords are entered and resulting URL are provided to watermarkdetector-enabled web browsers. Of course, interfacing with a searchengine can be automated as well.

Interface 102 also preferably interfaces with modules 110 (which mayinclude some human interaction) to assist in digging deeper intowebsites, e.g., websites including databases and FlashMedia. Modules 110may also provide the systems with addition URLs to visit. These URLs maybe directly provided to web crawler 120, but are preferably controlledby control panel 102.

Results from web crawler 120 (and reports from distributed web crawlers)are provided to a database 130 for customer reports or for furtheranalysis.

Search Engine Categorization

Search engines employ web crawlers to categorize web pages. For example,website text is obtained by a crawler and used to create keywordindexing. Website owners can also register a website by listing the URLand keywords. An improvement is to include a digital watermark analysisin the registration or categorization process. For example, the searchengine's web crawler employs a digital watermark reader and scans atarget website for digital watermarking. A digital watermark includes aunique identifier, and perhaps text. The identifier and/or text are usedas keywords when cataloging the target website. For example, the searchengine may associate a web address with a watermark numeric identifierand any text carried by the watermark, and may even indicate that thewebsite includes digital watermarking. The watermark-based keywords aresearchable along with any keywords derived from text or HTML found onthe website.

As a variation of the above categorization, content can include XMLtags. The tags can include a field which indicates that one or moreitems of content on a website include digital watermarking. The webcrawler/search engine need not decode the watermarks; but rather,determines from the XML fields (or header data) that the websiteincludes digital watermarking. The web crawler or associated searchengine includes a “watermarking is present” indicator as a keywordassociated with the website. Then, a search engine keyword search mayinclude all websites including “watermarking is present,” plus anyrelevant keywords (e.g., “Beagles”). Resulting website listings can besearched for digital watermarking.

Mobile Applications

Another searching tool facilitates communication with a plurality ofmobile devices and leverages search results generated by the variousmobile devices. Say, for example, that 23-year old Ginger goes clubbingon Saturday night. She finds her way to her favorite hangout and meetsup with three of her closest friends. The music is loud and conversationis stifled through the noise and haze. But wireless communication isuninhibited. Ginger—as always—has packed along her wireless device(e.g., Pocket PC, Blackberry, cell phone, etc.). Her device is, e.g.,BlueTooth enabled and readily communicates with similar devices carriedby Ginger's friends. (Long before, Ginger and her friends establishedpasswords or shared security protocols that enabled securecommunication; else anyone standing nearby with a wireless device mightbe able to sniff contents on their devices). Ginger's devicecommunicates with the other devices to see whether they have recentlyperformed any searching, and if so, what the nature of the searchingwas. Ginger can preset search topics (key terms or identifiers) in herwireless device. Instead of presetting search topics, Ginger's wirelessdevice can automatically generate search topics based on Ginger's webbrowsing history or past internet queries. One setting can be simply tocopy any search results carried out by the other devices. Ginger'sdevice uses these preset search topics to sniff other devices and see ifthey have found anything related to Ginger's search terms.

One friend, Kim, performed a targeted search, yesterday, for musicpenned and performed in the late 1980's by an obscure Australianrock-band, Aintitnice. The search results (and maybe even correspondingcontent like audio files) are stored in a search results or shareddirectory. (The search need not be carried out on Kim's mobile device,but instead, can be carried out on Kim's home computer, with the searchresults being communicated to Kim's mobile.) Ginger likes Aintitnicealso, and has entered the group as a search term in her mobile device.Ginger's wireless device negotiates with Kim's device to obtain thesearch results and/or even the audio files. (If the audio files arerights protected, Ginger's device can negotiate with an online server toobtain the necessary rights to play the music. For example, the audiofile may include a digital watermark that is used to link to the onlineserver).

Self selection by Ginger (e.g., being friends with Kim and presettingAintitnice) and proximity (e.g., clubbing with certain friends) enablemobile searching.

A few possible combinations of this mobile device searching include,e.g.:

A1. A method of searching comprising:

from a first mobile device, wirelessly querying a second mobile deviceto determine whether the second mobile device has internet searchresults relating to predetermined search criteria; and

receiving at least a subset of the search results.

A2. The method of A1, wherein the first device also queries to determinewhether the second mobile device has content related to thepredetermined search criteria.

B1. A method of searching comprising:

receiving search criteria in a first, handheld mobile device;

upon sensing of a second, handheld mobile device by the first, handheldmobile device, automatically and wirelessly querying the second,handheld mobile device to determine whether the second, handheld mobiledevice has any content stored thereon corresponding to the searchcriteria; and

receiving content corresponding to the search criteria from the second,handheld mobile device.

A few other combinations of the above sections include:

C1. A method of searching a network for watermarked content comprising:

receiving data representing a visible pattern;

searching the network for content corresponding to the visible pattern;

analyzing content identified as corresponding to the visible pattern fordigital watermarking;

obtaining at least one watermark identifier from the digitalwatermarking; and

reporting at least one watermark identifier and a corresponding networklocation when digital watermarking is found.

C2. The method of C1, wherein the visible pattern comprises a companylogo.

C3. A method of searching a network for watermarked content comprising

accessing a remote server to obtain a list of network locations;

searching the network locations for digital watermarking during periodsof computer user inactivity;

reporting to the remote server at least one watermark identifier and acorresponding network location when digital watermarking is found.

C4. A method of searching a network for watermarked content comprising:

accessing a remote server to obtain search criteria;

searching the internet for digital watermarking as a background processduring periods of computer user activity;

reporting to the remote server at least one watermark identifier and acorresponding network location when digital watermarking is found.

C5. The method of C4, wherein search criteria comprises an instructionto search internet content accessed by the user.

C6. The method of claim C4, wherein the search criteria compriseskeywords.

C7. The method of C6, further comprising automatically accessing anetwork search engine, providing the keywords to the network searchengine, and obtaining there from a listing of URLs associated with thekeywords, wherein said searching comprises searching the URLs.

C8. A system to direct network searching for watermarked contentcomprising:

a website interface to receive at least one of keywords and networklocations from a customer;

a website interface to communicate with a plurality of distributedwatermark detectors;

a controller to control communication of keywords and network locationsto the plurality of distributed watermark detectors; and

a database to maintain information associated with digital watermarkingand corresponding network locations.

C9. A system to direct network searching for watermarked contentcomprising:

a website interface to receive at least one of keywords and networklocations from a remote customer;

a web browser including or cooperating with a digital watermarkdetector;

a controller to communicate keywords and network locations to a webbrowser, wherein the web browser searches locations associated with thekeywords or the network locations; and

a database to maintain information associated with digital watermarkingand corresponding network locations.

Desktop Searching

Another aspect of the invention is a desktop searching tool thatprovides efficient media (e.g., audio, images and video) searching andcataloging. The tool can also provide metadata refreshing capabilitiesas well.

We start with a searching tool 201 (e.g., a software program orapplication) that resides on a user's computer 200 (FIG. 2). Thesearching tool includes two primary software components—an indexing tool202 and desktop searching tool 204. Of course, tools 202 and 204 neednot be separate components or software application, but are referred toseparately here to ease discussion of their individual functions. Thesoftware can be written in any language available to softwareprogrammers such as C, C++, Visual Basic, Java, Python, Tcl, Perl,Scheme, Smalltalk and Ruby, etc.

The indexing tool 202 combs through the user computer (or home network)in search of image, audio or video files. The indexing tool 202 catalogsits findings in one or more indices (e.g., it creates an index). An“index” contains a searchable listing or collection of words, numbersand characters and their associated files and locations. A user thensearches an index—instead of the entire computer—when she wants to finda file including a keyword. The search is carried out with DesktopSearching Tool 204. We mention here that we sometimes refer to bothimage and video files as “imagery.” Our use of the term “imagery” isalso broad enough to cover multimedia files as well.

The desktop searching tool 204 provides a user interface (e.g., desktopwindow or HTML based interface) through which a user queries an index tofind specific imagery or audio files or metadata associated therewith.Imagery or audio files are typically defined by a content portion and ametadata portion.

A user is preferably able to select storage areas to search and catalogby the searching tool 201, e.g., C drive, certain files or directories,and/or removable media (zip drive, external hard drive, DVD drive,attached MP3 player or jump drive (flash memory, USB drive), etc). Ofcourse, the user could select her entire computer or home network. Thesearching tool 201 can be preferably placed in a background searchingmode.

When operating in a background searching mode, the searching tool 202searches the computer while a user works on other applications (e.g.,akin to common anti-virus software that routinely looks at all incomingfiles). This background mode preferably filters new files as they arecreated or received by the user's computer or home network.

To simplify the discussion going forward we'll focus on imagery files.But the reader should not presume that our inventive techniques arelimited to just image or imagery files. Instead our techniques alsoapply to audio and rich content (e.g., MacroMedia flash files), etc.

Our indexing tool searches for image files, e.g., as identified by theirfile extensions *.gif, *.jpg, *.bmp, *.tif, etc. (If searching for audioor video files, we might search for *.au, *.wmv, *.mpg, *.aac, *.mp3,*.swf, etc.)

An image is indexed once it is located. To do so the image is openedsufficiently (e.g., perhaps without accessed any compressed imageportion) to access a metadata portion, if any. The metadata can beprovided for inclusion in a searchable index. For example, consider animage named “Falls.jpg,” with metadata including a descriptive phrase:“Picture of Falls taken near Silver Lake, Mont.” The file name and thedescriptive phrase are added to the desktop search index, along with thefile location and any other metadata in the descriptive phrase.

This first implementation works best when the searching tool 201cooperates with a desktop searching index (e.g., MSN Desktop Search)through an application program interface. For example, when the DesktopSearch encounters an image file it calls searching tool 201, or passesthe image file or file location to searching tool 201. In somealternatives, we use image searching software from IFilterShop LLC(available on-line at www.ifiltershop.com) as a component of indexingtool 202. The IFilterShop software would help to search images formetadata associated therewith. Such metadata is added to an index to besearched by a desktop searching tool 204.

In a second implementation, indexing tool 202 creates an HTML file (orXML, Word, or other text searchable file) for each image file searched.The HTML file is preferably stored in the same directory as the imagefile, or in a directory that is accessible to a searching tool. The HTMLfile includes the image file name (“Falls.jpg”) and a listing of anyterms (“Picture of Falls take near Silver Lake, Mont.”) and othermetadata (time, date taken, camera parameters, geo-coordinates, etc.).The HTML file preferably includes a similar name, but with a differentextension (e.g., “Falls.dwm.html”). We can optionally include (orassociate) a thumbnail representation of the JPEP image in the HTML fileas well.

The HTML file is searchable. For example, indexing tool 202 (or theGoogle and MSN desktop searching tools) are able to search the HTML filefor metadata (e.g., text), and once found, the searching tools add themetadata to their desktop index.

Digital Watermarks

In both the first and second implementations of the previously discusseddesktop searching an image file is preferably searched for an embeddeddigital watermark. That is the indexing tool 202 includes or cooperateswith a digital watermark detector. If found, the HTML file is providedwith a watermarking indicator (e.g., text, number or graphicalindicator) to show that the image file is watermarked and whatinformation is carried by the watermark (e.g., a plural-bit identifieror message).

Thus, a digital watermark—embedded in an image—becomes searchable by adesktop searching tool.

If a watermark is not found in an image, one can be embedded therein ifdesired.

A watermark can also be used as “the” identifier to link between animage and an on-line metadata repository as further explored below.

Watermark-Based Refreshing

In U.S. patent application Ser. No. 09/482,786, filed Jan. 13, 2000, andin its parent applications, we refer to a metadata repository and usinga steganographic identifier to access the metadata repository.

Related implementations are now provided.

We start with the premise that metadata will—inevitably—becomedisassociated with its underlying content. Scaling, cropping, editing,transforming and transmitting content increases the chances ofseparating metadata from its content.

A digital watermark provides the persistent link between metadata andcontent.

One aspect of our invention is a metadata “refresh” or synchronization.Desktop searching tool 201—as part of the indexing process—checks with ametadata repository to ensure that metadata associated with an image iscurrent or up to date. (As will be appreciated, these refreshing orsynchronization techniques can also be extended to internet searchingtools, like Google and Yahoo!, as well. A search engine, after or partof a search, can ask a searcher whether they would like to populatemetadata for a particular image, audio or video found. The methods andsystems detailed below can be used for such populating.)

In particular, the desktop searching tool 201 queries a metadatarepository 210 (FIG. 3) to see if there is any metadata associated withan encountered image.

The repository 210 can be stored locally on the user's computer 200, butmore likely the repository 210 is accessed over a network (e.g.,internet or cellular network).

If an encountered image includes a digital watermark identifier embeddedtherein, the watermark identifier is communicated to the metadatarepository 210. The identifier is used to index into the repository 210and locate any information associated therewith. The information iscommunicated to the searching tool 201 for indexing. The informationstored in the repository is checked against the image metadata. If therepository information is the most current or up to date, it is accessedand indexed (and perhaps stored or associated with the image on theuser's computer). If, however, the image includes the most up to datemetadata, the image metadata is preferably copied to the metadatarepository and cataloged according to the watermark identifier. Relativemetadata “freshness” can be determined, e.g., by a metadata timestamp oreven a “last updated” file indicator. Or if no file metadata is found(another case of unfreshness), metadata from the repository is providedfor indexing and associated with the image file.

Since a user is not so trusting, to simply except new metadata or freshcontent, a hash or other reduced-bit identifier can be used to verifythe veracity of content and metadata. For example, say a headerindicates the underlying content is a song by the Eagles. The header caninclude a hash of the song to allow verification of the contents andheader information. The hash is provided to a trusted third-partyrepository along with the metadata. The hash is authenticated and themetadata (and song) are then deemed trustworthy.

The searching tool 201 can periodically check with the metadatarepository 210 to ensure that the image metadata (and index of suchmetadata) is up to date. A graphical user interface may also provide aselectable button, allowing a user to select a feature to continuously(or frequently) query the metadata repository 210 to ensure metadatafreshness.

As an alternative implementation, the searching tool 201 inquireswhether an encountered image itself is stored in repository 210. If not,the searching tool provides a copy of the image to the repository 210.Then, both the metadata and image are stored in the repository 210. Asearch index can be updated to reflect that the image itself has beenstored in the repository 210. (In some cases the image is removed fromthe user's computer when it is copied to the repository). An imageregistration can be automatically carried out by the searching tool 201.For example, the registration may include association of the image tothe user's account or assignment of a unique identifier (e.g., via adigital watermark, fingerprint or hash).

Consider some additional watermark-based metadata gathering examples.

A fledging photographer takes a memory card full of pictures whilevacationing at Disneyland. Prior to taking her trip, the photographerprogrammed her camera (maybe which is incorporated into a cell phone) towatermark some or all pictures taken by the camera with the sameidentifier. The identifier is associated in the data repository 210 withkey words or information (e.g., vacation dates, location, family memberson the trip, on-line journal, etc.). Our searching tool 201, once itencounters the watermark identifier in a Disneyland picture, queries thedata repository 210 with the identifier in search of additionalmetadata. The key words or information are retrieved from the datarepository 210 and indexed for desktop searching. Thus, the identifieris used to generate additional metadata. The metadata can also beindexed in a searchable index.

Now suppose that the repository 210 is a public repository. The youngphotographer selects an identifier that is generally associated withDisneyland. That is, the photographer selects an identifier that peoplegenerally use when vacationing at Disneyland. Perhaps the watermarkidentifier is obtained through a trust metadata broker, one who istrusted to provide or obtain metadata associated with key metadata“ground truths” (e.g., like location, events, dates, etc.). A useridentifier can be used in connection with the selected identifier to aidin identifying the young photographer. The public or trusted metadatabroker populates or obtains data records associated with the identifier(e.g., people post Disneyland favorite memories, directions, MickeyMouse facts; or the trusted metadata broker obtains metadata itself,etc.). The searching tool 201, once it encounters the watermarkidentifier in a Disneyland picture, queries the data repository 210 withthe identifier in search of additional metadata. The data records areretrieved and indexed for desktop searching. (Of course, instead of apublic identifier, a semi-public identifier can be provided. Forexample, all members attending a family reunion can use the sameidentifier. Use of the term “same” includes a situation where awatermark has many payload fields, and the “same” identifier is includedin a predetermined field. In this multi-payload field situation, twowatermarks may include the same identifier but have differentinformation stored in different fields.)

Metadata Gathering

Metadata can be gathered using other techniques as well. For example, alocation of an image can be inferred from related clues. An image filenamed “DisneyLand001” was probably taken at Disneyland. The wordDisneyland is provided to an internet search engine or data repositoryto gather metadata. The metadata is provided to a desktop searching toolwhich updates the image file's metadata portion and indexes the newmetadata in a searchable desktop index.

A directory structure name and/or date and time information can be usedto gather metadata. For example, if searching tool 201 knows (e.g., froma metadata field or watermark date/time stamp) that a picture was takenon Feb. 14, 2005 at 8:30 pm, the searching tool can use this informationto gather related metadata. Perhaps the searching tool queries thephotographer's Outlook calendar or other calendaring software to seewhat was scheduled at that time (“Valentine's Day dinner at Jake's withJane”). This information is provided for indexing by the desktopsearching tool 201. Not only is this information provided for indexing,the information can be associated as metadata in the image file.

Or, if a user keeps an electronic journal or diary, a certain datewithin the journal or diary can be similarly queried. For example, wordsor terms within a journal entry are extracted, indexed and then storedas metadata. Still further, the searching tool can access financial orcheckbook software (e.g., Microsoft Money or on-line bank statements) tocheck receipts or entries around this time. (Interfacing with Outlook,MS Money, Word and Excel is straightforward to those skilled in the artgiven the public information about such programs and their interfaces.For example, Outlook can be accessed using Automation techniques fromjust about any program written with Microsoft Visual Basic. Othertechniques use application program interfaces, etc.).

A desktop searching tool 201 may also use an audit trail to gathermetadata. Suppose, for example, that a user receives a picture emailedfrom her brother Scott. The email trail (from whom and when received)can be used as metadata for the picture. (Recall from the discussionabove that all files can be searched when received. For example, theindexing tool 202 recognizes that a new image is received in an OutlookInbox. The email history and image are combed by the indexing tool 202to gather this information).

An internet history or cache is also looked at. For example, searchterms entered into an internet search engine are pulled from theBrowser's history or are cached and used as metadata for an image foundfrom the search.

Many of today's cameras are equipped with GPS units. GPS data generatedby these units can be stored in header or watermark information.Searching tool 201 uses the GPS data to locate related metadata. Forexample, GPS coordinates are extracted from an image and are provided toa geographical database. The coordinates are used to index the databaseand find metadata associated with the geolocation. The metadata caninclude a city name, historical information, current weather, buildingspecification, associated pictures, etc.

We can also gather metadata from general “inferences” made about animage. For example, we can look at metadata in adjacent pictures.Consider, for example, a directory that includes three pictures: photo1, photo 2 and photo 3. When gathering metadata for photo 2, searchingtool 201 looks at metadata associated with photo 1 and photo 3 tosupplement the metadata for photo 2. Chances are that the photographswere taken at or about the same time or at or around the same location.Similarly, timestamps are used to determine images that were taken nearone another—like within a 5 or 10 minute window. Chances are that imageswithin such a timeframe are related. This window can be expandeddepending on user preference (e.g., expanded to 7 days to cover aDisneyland vacation). Metadata associated with these images is used bythe searching tool 201 or associated with a target image.

GPS data and timestamps can be used to generate even furtherinformation. For example, a sports enthusiast snaps a few pictures whileattending the NCCA men's basketball semi-finals in Dallas. GPScoordinates and a timestamp are associated with the pictures (e.g., asan embedded watermark or header information). The GPS is used toidentify the location (e.g., sports arena) and the timestamp is used toidentify an event at the sports arena (basketball game). These terms canbe used as search terms to identify additional metadata, stories,scores, etc. associated with the event. This information is provided forassociation with the images.

Metadata Generation

We can also automatically generate metadata for an image.

Consider a cell phone that has a biometric sensor (e.g., a fingerprintscanner). (For example, LG Telecom, one of the largest wireless networkoperators in Korea, recently launched a biometric cell phone—the LP3800.Other manufacturers are providing competing cell phones.) A userpresents her finger for scanning by the cell phone. The user isidentified via the fingerprint. A searching tool 201 uses thisfingerprint identifier as photographer metadata. (For example thesearching tool 201 can query (e.g. via a wireless or Bluetooth sniff)the cell phone and inquire who the photographer was when the photo wastaken. The photo is identified to the cell phone camera by file name orother identifier. Or, if a photographer identifier is included in aphotograph's metadata, the searching tool 201 queries the cell phone tosee who the identifier corresponds with. If the biometric identifier hasbeen encountered before, the searching tool can use past cell phoneinquiry result instead of talking with the cell phone. Of course a humanfingerprint (or template there from) can be used as metadata itself.

Search tool 201 may also include or cooperate with a pattern recognitionor color analysis module. Metadata is generated through image patternrecognition. For example, the searching tool 201 analyzes an image witha pattern recognition module. The results of which are used as metadata.(For example, the pattern recognition module might return the term“tree” after analyzing a picture of a tree). We can also perform a coloranalysis of an image, e.g., calculating a 3-D color space histogram ofthe image. The histogram identifies predominate colors (e.g., red, pink,yellow, etc.). Predominate colors can be based on an image region or apercentage of an image including the predominate color. Or only the topthree or so colors are indexed for a particular image. One can imagine asearch request typed or spoken into desktop searching tool 204requesting a picture of grandma wearing her pink hat. The query mayspecifically include the terms “grandma” and “pink”. The term “pink”identifies those pictures having pink as a predominate color asautomatically determined from such color analysis. This subset iscross-check with all pictures including grandma as metadata. Theresulting set of pictures is identified for user perusal.

Other metadata can be inferred from image characteristics. A “dark”picture (as determined by a color or pixel analysis) might imply thatthe picture was taken at night or indoors.

Instead of pattern recognition or digital watermarking, searching tool201 may include or cooperate with a fingerprinting module. We use theterm “fingerprint” to mean a reduced-bit representation of an image likean image hash. The terms “fingerprint” and “hash” are sometimeinterchangeably used. A fingerprint is generated and is then used toquery a database where other images have been fingerprinted. Forexample, different pictures of the Empire State Building yield similar(or related) fingerprints. These pictures and their correspondingfingerprints are indexed in the database. While exact matches might notbe frequently found, those fingerprints that are deemed statisticallyrelevant are returned as possible matches. Metadata associated withthese fingerprints can be returned as well. (Fingerprinting andwatermarking can also be advantageously combined. For example, a digitalwatermark can be used as a persistent link to metadata, while afingerprint can be used for identification.)

Searching tool 201 may also include or cooperate with a facialrecognition module. Facial recognition software is used to identifypeople depicted in images. Once trained, the facial recognition softwareanalyzes images to see whether it can identify people depicted therein.Names of depicted people can be indexed and associated with the image.Or individual profiles (name, birth date, family relation, etc.) can beestablished and associated with a person. Then, when the facialrecognition software identifies an individual, the individual's profileis associated with the image as metadata. (FIG. 4 shows one example ofthis method. Facial recognition software 401 analyzes an image 402 anddetermines that the image depicts Jane. A profile database 403 isinterrogated to obtain Jane's profile 404 (e.g., name, current age,birth date, etc.) and the profile 404 is associated with the image asmetadata.)

Metadata can also be generated by searching devices within a user's homedomain. For example, the searching tool 201 initiates communication(e.g., via Bluetooth or wireless connection) with the user's cell phone,which is equipped with a camera and GPS unit. The searching tool 201queries where the camera has taken pictures. The geolocations and timesof image capture can be used as metadata or to find metadata. Instead ofquerying the cell phone or other camera, the searching tool might talkwith a user's TiVo device, game console (e.g., Xbox or PlayStation),music player (e.g., an iPod or MP3 player) or PDA. Relevant information(e.g., journals, calendars, other images, music, video games, etc.)gathered from these sources can be used as metadata for a particularfile on the user's desktop.

User Selection

The searching tool 201 (FIG. 2) preferably includes one or more userinterfaces (e.g., as provided by tool 204) through which a user caninteract with the tool 201 and metadata found or indexed by the tool201.

For example, a user is preferably able to select, through desktopsearching tool 204, internet-based sites at which searching tool 201 islikely to find additional metadata. (The user can type in URLs orhighlight predetermined metadata websites.)

The user can also preferably set one or more filters through suchinterfaces. A “filter” is a software module or process that limits orscreens information that should be used as metadata. Filters allow auser to weed out potentially meaningless metadata. For example, onefilter option allows for only metadata gathered from the user's desktopto be associated with an image. Another option allows a user to setpreferred or trusted metadata sources. Metadata gathered from repository210 might be designated as being trusted, but metadata gathered from anautomatic internet search of text found in an image header might not betrusted. A related filter option allows a user to pre-rank metadatabased on source of the metadata. If the metadata is not of a sufficientrank, an image file is not augmented to include the new metadata and thelow-ranking metadata is not indexed. Yet another filter option allowsfor only metadata approved by a user to be associated with an image.

Gathered or generated metadata is preferably presented through aninterface for the user's review and approval. For example, metadata ispresented via a graphical window complete with check-boxes (see FIG. 5).A user simply checks the metadata she would like associated with animage and the searching tool 201 updates the metadata portion of animage file to reflect the user's selections. Instead of checkboxes auser can highlight metadata she wants to keep.

Directory View

Another feature of the present invention is a directory view. Files areoften arranged and graphically displayed by directories and folders.(Just click on “My Documents” in your computer directory and see how thefiles are arranged therein.)

An improvement arranges and graphically displays files according totheir metadata. For example, based on information gathered by searchingtool 201, images arranged and graphically displayed on a computerdisplay according to metadata associated therewith. The metadatacategories can change based on user preference, but we provide a fewexamples below.

A user selects three broad metadata categories, vacations, professionaland family.

A program (or operating system) queries an index provided by searchingtool 201. All images including metadata identifying them as a “vacation”image are associated with the vacations directory, and all imagesincluding metadata identifying them as “family” are associated with thefamily directory.

The user can change the “file directory” view by changing the metadatacategories. The user can also establish subdirectories as well (e.g.,Disneyland and Niagara Falls metadata displays within the vacationdirectory).

Image are arranged and displayed in a metadata structure and not in atypical directory tree fashion. If a user changes the metadata request,the desktop arrangement is altered as well.

Visual presentation of a directory view can also be changed, e.g.,according to a style sheet associated with a particular type of metadataor media. Style sheets can vary from family member to family member (orbetween Windows login profiles). Music can also be represented accordingto its content. For example, music with a particular rhythm or harmonycan be presented uniquely or according to a style sheet, etc.

One of the many possible combinations of the above file directoryincludes:

D1. A graphical user interface, stored and running on a computer,comprising:

a first module to present a graphical representation of files through acomputer display;

a second module to determine metadata associated with each of the filesfor display;

a third module to graphically organize the files for display accordingto their metadata.

Metadata Authoring

A metadata authoring tool 206 (e.g., a software application) isdescribed with reference to FIG. 6. The authoring tool 206 allows a userto annotate and associate metadata with multimedia content. While mostimage editing software (e.g., Digital Image Suite from Microsoft)provides metadata authoring capabilities, we provide a few improvementsherein.

One improvement is the ability to “paint” an image or group or imageswith predetermined metadata. For example, in a software applicationsetting, we provide a metadata toolbar that provides different metadatachoices, e.g., terms like “vacation,” “family,” or profiles (“Jane'sindividual profile”), etc. Selecting (clicking) a metadata category fromthe metadata toolbar enables us to paint an image or file directory withthe metadata. (One can imagine that the metadata selection makes themouse cursor appear as a paintbrush. We then literally “paint” an imagewith the selected metadata. The image or directory icon representation(or thumbnail) can even turn a color associated with the metadata toprovide user feedback that the metadata has been attached to the image.)Behind the scenes, the user selection of metadata and a target imagetell the authoring tool 206 which metadata is to be added to a metadataportion of an image file. The metadata portion is rewritten or added toreflect the “painting.”

Even More Desktop Searching

Returning to the topic of desktop searching, in another implementation,we provide an image (and/or audio and video) searching tool (e.g., acomputer program written in C++). The image searching tool resides on auser's device (e.g., computer, network server, iPod, cell phone, etc.)and crawls though files and folders in search of images. For example,the searching tool searches for image files, e.g., as identified bytheir file extensions *.gif, *.jpg, *.bmp, *.tif, etc. (If searching foraudio or video files, we might search for *.au, *.wmv, *.mpg, *.aac,*.mp3, *.swf, etc.). In another example, a user (or operating system)identifies image directories and the searching tool combs through eachof these identified directories.

Once identified, and with reference to FIG. 7, the searching tool opensan image and searches the image for an embedded digital watermark. Thesearching tool may include or call a watermark detector. If found, thewatermark information (e.g., plural-bit payload) is provided to or isincluded in a first file, e.g., an XML file. The first file preferablyincludes the same file name, but has a different file extension. Theimage is further evaluated to obtain metadata there from (e.g., EXIFinformation, header information or other metadata). The metadata isprovided to or is included in the first file. The first file may includethe same tags or identifiers as were originally included in the image(or audio or video).

Upon encountering a digital watermark, the searching tool may query oneor more online metadata repositories to determine whether there existsadditional metadata associated with the image. Such online metadata maybe downloaded to the first file. Of course, filters or criteria may beused to restrict which online metadata is accepted. For example, onlythose packets or groupings of metadata that are signed by a trusted orrecognized source may be accepted for inclusion in the first file. Ordifferent metadata fields or tags can include a last modified or timestamp indicator. That way, if the online-metadata includes a redundantfield or tag, the most recent version (either associated with the imageor online) of the metadata is used. Still further, a user can specifywhich sources of metadata should be trusted and included.

A watermark identifier can also facilitate “bi-directional” metadatapopulation. That is, a watermark identifier can link to an onlinerepository of metadata, and in particular, to a particular image orassociated metadata. Metadata can be uploaded to the online repositoryand associated with the image metadata via the watermark identifier.(Watermark-based network navigation is discussed, e.g., in assignee'sU.S. patent application Ser. No. 09/571,422, mentioned above.)

Returning to FIG. 7, a second file (e.g., HTML) is created. The secondfile name preferably includes the same file name as the first file andimage, but with a different file extension. The second file preferablyincludes information from the first file. For example, if the first fileincludes a storage location for the image, the second file may include ahyperlink to the image (based on the storage location). As discussed insome of the implementations above, the second file may also include arepresentation of the image, or if video or audio, perhaps a sample orsnippet of the audio or video. The second file can be configured by auser to include some or all of the information from the first file. Thisis advantageous, e.g., if the user wants to limit viewing of camerasettings. (Behind the scenes, an XML parser cooperating with a stylesheet or “skin” can be used to interpret the first file and populate thesecond file in accordance with the style sheet. In other implementationsunderlying content itself is used to determine how to populate a secondfile. Audio content having a certain rhythm or melody is displayedaccording to a first predetermined style, while content having othercharacteristics are displayed according to a second, different style.)

The creation of the HTML file typically triggers indexing by a desktopsearching tool (e.g., Google or Yahoo, etc.). The metadata is added toan index, effectively allowing searching of the image. In someimplementations, of course, the functionality of the above search toolis integrated with the desktop searching tool. In other implementations,the searching tool plugs-in with the desktop searching tool. In stillother implementation, a searching tool cooperates (or operates from) aproxy server or network hub.

(We note here that some desktop searching tools, such as Google'sDesktop Searching tool allows for registering of certain file “types”(e.g., JPEG, etc.). The first file mentioned above can be given a uniquefile extension (or type). That way, a desktop searching tool can be toldto ignore the first file when indexing so as to avoid redundantresults.)

The image searching tool can compare a “Last modified” date to determinewhether to index a particular image. For example, an image's lastmodified date can be compared to a last modified date of a correspondingfirst file. If the image's modification date is later than the firstfiles, the image is again analyzed to obtain the watermark and metadata.The first file is updated, along with the corresponding second file.

Blogs

Watermarks can also be used to facilitate and link to so-called on-lineblogs. (A blog is information that is published to a web site. So-called“blog scripting” allows someone to post information to a Web site.)

Consider a photo (or audio or video) that includes a digital watermarkembedded therein. A watermark reader extracts the watermark and links toan on-line resource (e.g., a URL). An improvement is that the digitalwatermark links to a blog or blog thread (or conversation). The blog maybe stored, e.g., as a file. Consider that the watermark includes orreferences a URL of an online photo blog site, e.g., akin to Flickr(see, e.g., www.flickr.com). The watermark can link to a specificpicture or account at flicker, and perhaps even a particular blogthread. For example, consider a photo depicting a home office, completewith a computer, monitor and chair. There may be several different blogthreads (or conversations) being posted about the items depicted. (Maybesomeone likes the chair, and wonders whether it will provide sufficientlumbar support. A conversation or thread continues on this topic.) Awatermark—perhaps representing an image region that depicts the chair,or that is otherwise linked to the chair or thread—is used to link tothe particular thread. A separate watermark (or watermark component) canbe embedded in the image to represent a particular thread. The watermarkpayload or component information may even include an identifier thatwill link to subject matter line—displayable to a user—to allow user'sto pick which blog thread they would like to consider. If the photocontains multiple such watermarks, each of the corresponding subjectmatter lines can be displayed for selection. Thus, the watermark becomesthe root of each blog and blog thread. (Perhaps as a prerequisite tostarting a blog thread, the conversation is assigned a watermarkidentifier or component, and the component is embedded in theimage—perhaps region specific—when the blog or response is posted.)

In other implementations, each person who comments to a blog is assignedan identifier (or even a particular, unique watermark signature). Theperson's watermark is embedded in the image when they blog or otherwisecomment on the photo.

More on Blogs

At their roots, “photoblogs” are simply blogs with pictures. In mostcases the pictures are the anchors. They grab attention, set tone andact as bookmarks. (See, e.g., www.photoblog.org).

So, on the one hand you can simply post an image as part of a log on theweb, providing humor, illustration, documentation or an anchor for aconversation. The conversation could be about a vacation location,person, children, family, places or anything else topical andphotogenic.

Digital watermarking brings a new twist with improvements. Watermarkingmakes the photo the centerpiece of a photoblog. A watermarked photobecomes an agent to the blog and a portal that can be revisitedrepeatedly. The photo could be distributed as a pointer to the blogitself. The photo catches the attention of the recipient, and throughthe digital watermark links back to a blog server (or network resourceat which the blog is hosted). One can imagine that the blog is hosted(e.g., you must go to the website to read) or downloadable (e.g., sortof like the good old newsgroup concept). By dragging and dropping thephoto on a blogging client or other application, one adds the blog tothe client or application. (Behind the scenes, a watermark detectorreads a watermark identifier from the dragged-and-dropped photo. Thewatermark identifier is used to link to the on-line blog (orconversation). For example, the identifier is used to identifier a filestorage location of the blog, or a network location hosting the blog(e.g., URL). The blog is obtained or downloaded to the location. Inother cases, instead of downloading the entire blog, a link to the blogis stored at the application or client.)

Consider blog initiation. A user uploads an image to a blogging site tostart a blog and writes a first entry. The site automatically watermarksthe image with an identifier, linking the photo to the blog (or addingit to an existing blog). With the blog created, the user may(optionally) right-click, e.g., to send the image (and blog) to afriend. The e-mail including the watermarked photo invites friends torespond. They are linked to the original blog through the watermarkidentifier.

This functionality can be incorporated with desktop searching tools.

When a watermarked image is noticed by a desktop searching tool, thatimage is checked to see if there's an associated blog, e.g., by queryingan on-line blog site associated with the watermark or evaluating a“blog-bit” carried by a watermark payload. (A watermark payload mayinclude many fields, with one of them identifying or linking to aparticular blogging site.). The desktop searching tool (or photohandling software including, Photoshop, web browser, etc.) preferablyprovides a user indication (e.g., “go to blog” link shows up). Viewerscan navigate over to read the blog via the watermark identifier. Theimage becomes linked or “bookmarked” to the blogging thread.

A watermark reader or desktop searching tool can include a right-clickfeature that allows addition of a blog entry on bloggable images (afeature determined by the watermark). Thus an image may appear anywhere,on a home computer or cell phone, and act as a gateway to the blog forreading or adding to the blogging thread.

The basic association of a blog with an image can happen, e.g., when aphoto is registered at a photo-repository or online site. The act ofregistering a photograph—or watermarking the photograph—can create ablog, and over time, provide a more generalized brokerage to any blogthat is registered. Any image can be “bloggable”. Over time,photographers can create blogs around their collection as a way ofmarketing or communicating. One can even imagine blogs that are private(e.g., password or biometric protected) as a means of interacting with afriend or client.

A watermark preferably survives into print, and thus a relationship iscreated between printed images and (photo) blogs. (In someimplementations a blogs is not created until an image is printed. But inany case, watermarking adds power to print that passes through awatermarking step, giving it a unique identity.)

As a practical application a web-based user interface is created. A userpresents a watermarked picture (or just a watermark identifier extractedfrom said picture) to the interface via the web. If receiving thepicture the website extracts a watermark identifier there from. Thewatermark identifier is provided to a basebase or index to locateinformation associated therewith. For example, the picture wasoriginally associated with one- or more text-based blogs. A currentlocation of the blogs are found and provided to the user through theinterface.

A few possible combinations of the above blogging implementationsinclude:

E1. A method of associating a blog with media comprising:

embedding a digital watermark in an image or audio;

associating at least a portion of the digital watermark with anetwork-hosted blog.

E2. The method of E1, wherein the watermark comprises plural datafields, with at least one of the fields including or pointing to anon-line address at which the blog is hosted.

E3. The method of E1 wherein the blog comprises an on-line conversation.

E4. A method of associating an online blog with media comprising:

decoding a digital watermark from the media;

accessing an on-line repository associated with the watermark; and

accessing the blog associating with the media.

Concluding Remarks

Having described and illustrated the principles of the technology withreference to specific implementations, it will be recognized that thetechnology can be implemented in many other, different, forms. Toprovide a comprehensive disclosure without unduly lengthening thespecification, applicants hereby incorporates by reference each of thepatent documents referenced above.

The methods, processes, components, modules, filters and systemsdescribed above may be implemented in hardware, software or acombination of hardware and software. For example, the watermark dataencoding processes may be implemented in a programmable computer or aspecial purpose digital circuit. Similarly, watermark data decoding maybe implemented in software, firmware, hardware, or combinations ofsoftware, firmware and hardware.

The methods, components and processes described above (e.g., desktopsearching tools and metadata generation and gathering tools) may beimplemented in software programs (e.g., C, C++, Visual Basic, Java,Python, Tcl, Perl, Scheme, Ruby, executable binary files, etc.) executedfrom a system's memory (e.g., a computer readable medium, such as anelectronic, optical or magnetic storage device).

The section headings are provided for the reader's convenience. Featuresfound under one heading can be combined with features found underanother heading. The various example “combinations (e.g., C1, D1, etc.)are provided by way of example only. Of course, many other combinationsare possible given the above detailed and enabling disclosure.

Our use of the term “desktop” should not be construed as being limiting.Indeed, our “desktop” searching modules and our metadata generation andgathering methods can be employed on laptops, handheld computingdevices, personal (or digital) video recorders (e.g., think TiVo), cellphones, etc. We can even store our metadata index or searching tools onconsumer electronic devices like MP3 players, iPods, TiVo devices, gameconsoles (e.g., XBox), etc.

The particular combinations of elements and features in theabove-detailed embodiments are exemplary only; the interchanging andsubstitution of these teachings with other teachings in this and theincorporated-by-reference patents/applications are also contemplated.

What is claimed is:
 1. A method of associating Internet content withmedia, the method comprising: decoding, via a processor, an embeddeddigital watermark from media; searching, via the processor, an on-linerepository associated with the embedded digital watermark; andproviding, via the processor, a list of Internet content associated withthe media based on results from searching of the on-line repository,wherein the Internet content includes one or more on-line blogs, whereinthe watermark comprises plural data fields, with at least one of thefields including or pointing to an on-line address at which the on-lineblog is hosted.
 2. The method of claim 1, wherein the embedded digitalwatermark links to a specific picture on an online photo site.
 3. Themethod of claim 1, wherein the embedded digital watermark includes aroot for a blog thread.
 4. The method of claim 1, wherein the embeddeddigital watermark includes a payload having an identifier that links toa subject matter line.
 5. The method of claim 1, further comprisingreceiving a selection of Internet content and triggering, via theprocessor, a link to the on-line resource.
 6. The method of claim 1,wherein the media includes a plurality of embedded digital watermarksand each of the corresponding subject lines for the plurality ofembedded digital watermarks are presented for selection.
 7. Anon-transitory computer-readable medium having instructions storedthereon that, if executed by a computing device, cause the computingdevice to perform operations comprising: instructions to decode anembedded digital watermark from media; instructions to search an on-linerepository associated with the embedded digital watermark; instructionsto provide a list of Internet content associated with the media based onresults from searching of the on-line repository; and instructions toreceive a selection of Internet content and instructions to trigger, viathe processor, a link to the on-line resource, wherein the watermarkcomprises plural data fields, with at least one of the fields includingor pointing to an on-line address at which the on-line resource ishosted.
 8. The computer-readable medium of claim 7, wherein the Internetcontent includes one or more on-line blogs.
 9. The computer-readablemedium of claim 7, wherein the embedded digital watermark includes apayload having an identifier that links to a subject matter line. 10.The computer-readable medium of claim 7, wherein the media includes aplurality of embedded digital watermarks and each of the correspondingsubject lines for the plurality of embedded digital watermarks arepresented for selection.
 11. A wireless device comprising: a processorconfigured to: decode an embedded digital watermark from media; searchan on-line repository associated with the embedded digital watermark;and provide a list of Internet content associated with the media basedon results from searching of the on-line repository, wherein theInternet content includes one or more on-line blogs, wherein thewatermark comprises plural data fields, with at least one of the fieldsincluding or pointing to an on-line address at which the on-line blog ishosted.
 12. The device of claim 11, wherein the embedded digitalwatermark includes a payload having an identifier that links to asubject matter line.
 13. The device of claim 11, wherein the processoris further configured to receive a selection of Internet content and totrigger a link to the on-line resource.
 14. The device of claim 11,wherein the media includes a plurality of embedded digital watermarksand each of the corresponding subject lines for the plurality ofembedded digital watermarks are presented for selection.